A major goal of systems developmental biology is to create datasets and models that describe, simulate and predict the full complement of gene regulatory interactions during embryogenesis. Such datasets and models are essential to fully understand how genomic information is translated into anatomical structure. Reductionist approaches have identified interactions among dozens of genes, but technical limitations have hindered the systems-wide elucidation of regulatory relationships at both high spatial resolution and whole-genome scale. This project will address this challenge and use novel technologies that enable large-scale mutagenesis and genome-wide expression profiling of single cells to generate gene regulatory network models. The zebrafish blastula will be used as a vertebrate model system, because of its similarities to mammalian embryos and the applicability of powerful genetic, imaging and genomic approaches. The project builds on a long-standing collaboration that combines the Schier lab's expertise in developmental biology, imaging and genetics with the Regev's lab expertise in computational biology, genomics and systems biology. Optimized one-generation CRISPR/Cas9 genome editing will be used to generate mutants for dozens of transcription regulators expressed during early embryogenesis. Mutants will be characterized by generating whole-genome high-resolution gene expression atlases using a novel technology called Seurat. Seurat combines single-cell RNA sequencing with computational mapping of cells to specific regions and cell types in the embryo. The resulting transcriptome maps serve as the inputs to generate models for gene regulatory network activity using clustering-based and Bayesian modeling approaches. Regulatory interactions predicted in silico will be tested in vivo by analyzing gene expression upon perturbation of transcription regulators. The project fulfills the stated purpose of PAR-15-020 to complement the reductionist focus of modern developmental biology and provide a more comprehensive understanding of the causal relationships leading to normal and abnormal embryogenesis. The gene regulatory interactions discovered in this project will help inform programming and reprogramming approaches and will identify candidate interactions that might be involved in the development of birth defects. The project will generate extensive high-quality datasets and atlases for developmental and systems biologists and provide a framework to dissect gene regulatory networks in other systems.